![In 1840 : Henle proposed postulates for causation that were expanded by Koch in the
1880s.
The postulates for causation were as follows:
1. The organism is always found with the disease.
2. The organism is not found with any other disease.
3. The organism, when isolated from one who has the disease and cultured through
several generations, produces the disease (in experimental animals).
• Koch added that “Even when an infectious disease cannot be transmitted to animals,
the ‘regular’ and ‘exclusive’ presence of the organism [postulates 1 and 2] proves a
causal relationship.”
• These postulates, although not perfect, proved very useful for infectious diseases.
• However, as apparently noninfectious diseases assumed increasing importance
toward the middle of the 20th century, the issue arose as to what would
represent strong evidence of causation in diseases that were generally not of
infectious origin.](https://image.slidesharecdn.com/causation-241104040846-1e44e26d/85/causation-main-association-to-causaty-slide-18-320.jpg)
causation.main.association to causaty slide
- 1. From Association to Causation: Deriving Inferences From Epidemiologic Studies Dr. Habibeh Ahmadipour Associate Professor of Community Medicine
- 2. Learning Objectives • To describe a frequent sequence of study designs used to address questions of etiology in human populations. • To differentiate between real and spurious associations in observational studies. • To define the concepts of “necessary” and “sufficient” in the context of causal relationships. • To present guidelines for judging whether an association is causal.
- 3. What approaches are available for studying the etiology of disease? Approac hes Animal studies In vitro studies observation s in human populations
- 4. Epidemiologic Studies Observational Descriptive Cross sectional Analytic Case control Cohort Interventional Experiment al Quasiexper imental Epidemiologic Studies classification
- 7. A two-step process is followed in carrying out studies and evaluating evidence: 1. We determine whether there is an association or correlation between an exposure or characteristic and the risk of a disease To do so, we use: a. Studies of group characteristics: ecologic studies b. Studies of individual characteristics: cohort, case-control, and other types of studies 2. If an association is demonstrated, we determine whether the observed association is likely to be a causal one.
- 11. • Is this distinction really important? • What difference does it make? If the relationship is causal, we will succeed in reducing the risk of colon cancer if we promote physical activity, both for the individual but also at the population level. However, if the relationship is due to confounding, then the increased risk of colon cancer is caused by factor X. Therefore increasing physical activity will have no effect on the risk of colon cancer. Thus it is extremely important for us to be able to distinguish between an association due to a causal relationship and an association due to confounding (which is non causal).
- 13. Types of causal relationships
- 14. NECESSARY AND SUFFICIENT The factor is necessary: Without that factor, the disease never develops The factor is sufficient: in the presence of that factor the disease always develops
- 15. Types of causal relationships
- 17. Evidence for judging whether an association is causal?
- 18. In 1840 : Henle proposed postulates for causation that were expanded by Koch in the 1880s. The postulates for causation were as follows: 1. The organism is always found with the disease. 2. The organism is not found with any other disease. 3. The organism, when isolated from one who has the disease and cultured through several generations, produces the disease (in experimental animals). • Koch added that “Even when an infectious disease cannot be transmitted to animals, the ‘regular’ and ‘exclusive’ presence of the organism [postulates 1 and 2] proves a causal relationship.” • These postulates, although not perfect, proved very useful for infectious diseases. • However, as apparently noninfectious diseases assumed increasing importance toward the middle of the 20th century, the issue arose as to what would represent strong evidence of causation in diseases that were generally not of infectious origin.
- 19. GUIDELINES FOR JUDGING WHETHER AN OBSERVED ASSOCIATION IS CAUSAL: 1. Temporal relationship 2. Strength of the association 3. Dose-response relationship 4. Replication of the findings 5. Biologic plausibility 6. Consideration of alternate explanations 7. Cessation of exposure 8. Consistency with other knowledge 9. Specificity of the association
- 20. 1. Temporal Relationship. It is clear that if a factor is believed to be the cause of a disease, exposure to the factor must occur before the disease develops. Fig. 14.17 shows the number of deaths per day and the mean concentration of airborne particles in London in early December 1952.8 The pattern of a rise in particle concentration followed by a rise in mortality and a subsequent decline in particle concentration followed by a decline in mortality strongly supported the increase in mortality being due to the increase in air pollution. Further investigation revealed that the increased mortality consisted almost entirely of respiratory and cardiovascular deaths and was highest in the elderly
- 21. • It is often easier to establish a temporal relationship in a prospective cohort study than in a case-control study or a retrospective (non concurrent) cohort study. • In the latter two types of studies, exposure information may need to be located or re- created from past records and the timing may therefore be imprecise. • The temporal relationship of exposure and disease is important: not only for clarifying the order in which the two occur but also in regard to the length of the interval between exposure and disease. • For example, asbestos has been clearly linked to increased risk of lung cancer, but the latent period between the exposure and the appearance of lung cancer is at least 15 to 20 years. • Therefore, if, for example, lung cancer develops after only 3 years since the asbestos exposure, it is probably safe to conclude that the lung cancer was not a result of this exposure.
- 22. 2. Strength of the Association: • The strength of the association is measured by the relative risk (or odds ratio).
- 23. 2. Strength of the Association: • The stronger the association, the more likely it is that the relation is causal. • For example, the relative risk for the relationship of high blood pressure (exposure) to stroke (outcome) is very high. • In a population-based study conducted in Sweden, the relative risk was found to be greater than 5.0 in individuals with severe hypertension. • There is little or no doubt that high blood pressure levels cause stroke.
- 24. 3- Dose-Response Relationship. As the dose of exposure increases, the risk of disease also increases. Fig. 14.18 shows an example of the dose-response relationship for cigarette smoking and lung cancer.
- 25. • Another example is given by the Swedish study mentioned previously, in which, using normal blood pressure levels as the reference category, the adjusted relative risk for stroke increased in a graded fashion from 2.84 in individuals with prehypertension to 3.90 in those with moderate hypertension to 5.43 in those with levels consistent with severe hypertension. • If a dose-response relationship is present, it is strong evidence for a causal relationship. • However, the absence of a dose-response relationship does not necessarily rule out a causal relationship. • In some cases in which a threshold may exist, no disease may develop up to a certain level of exposure (a threshold); above this level, disease may develop.
- 26. 4. Replication of the Findings: • If the relationship is causal, we would expect to find it consistently in different studies and in different populations. • Replication of findings is particularly important in epidemiology. • If an association is observed, we would also expect it to be seen consistently within subgroups of the population and in different populations, unless there is a clear reason to expect different results.
- 27. 5. Biologic Plausibility: • Biologic plausibility refers to coherence with the current body of biologic knowledge. • Examples may be cited to demonstrate that epidemiologic observations have sometimes preceded biologic knowledge. • Thus, as discussed in an earlier chapter, Gregg’s observations on rubella and congenital cataracts preceded any knowledge of teratogenic viruses. • Similarly, the implication of high oxygen concentration in the causation of retrolental fibroplasia, a form of blindness that occurs in premature infants, preceded any biologic knowledge supporting such a relationship. • Nevertheless, we seek consistency of the epidemiologic findings with existing biologic knowledge, and when this is not the case, interpreting the meaning of the observed association may be difficult. • We may then be more demanding in our requirements about the size and significance of any differences observed and in having the study replicated by other investigators in other populations
- 28. 6. Consideration of Alternate Explanations. • We have discussed the problem in interpreting an observed association in regard to whether a relationship is causal or is the result of confounding. In judging whether a reported association is causal: • the extent to which the investigators have taken other possible explanations into account • the extent to which they have ruled out such explanations are important considerations.
- 29. 7. Cessation of Exposure If a factor is a cause of a disease, we would expect the risk of the disease to decline when exposure to the factor is reduced or eliminated. Fig. 14.19 shows such historical data for cigarette smoking and lung cancer.
- 30. • When cessation data are available, they provide helpful supporting evidence for a causal association. • However, in certain cases the pathogenic process may have been irreversibly initiated and the disease occurrence may have been determined by the time the exposure is removed. • Emphysema is not reversed with cessation of smoking, but its progression is reduced.
- 31. 8. Consistency With Other Knowledge If a relationship is causal, we would expect the findings to be consistent with other data. For example, Fig. 14.21 shows data regarding lung cancer rates in men and women and cigarette smoking in men and women.
- 32. 9. Specificity of the Association • An association is specific when a certain exposure is associated with only one disease; this is the weakest of all the guidelines and should probably be deleted from the list. • Cigarette manufacturers have pointed out that the diseases attributed to cigarette smoking do not meet the requirements of this guideline because cigarette smoking has been linked to lung cancer, pancreatic cancer, bladder cancer, heart disease, emphysema, and other conditions.
- 33. • The possibility of such multiple effects from a single factor is not, in fact, surprising: regardless of the tissue that comprises them, all cells have common characteristics, including DNA, RNA, and various subcellular structures, so a single agent could have effects in multiple tissues. • Furthermore, cigarettes are not a single factor but constitute a mixture of a large number of compounds; consequently, a large number of effects might be anticipated. • When specificity of an association is found, it provides additional support for a causal inference. • However, as with a dose-response relationship, absence of specificity in no way negates a causal relationship.
- 38. GORDIS EPIDEMIOLOGY, SIXTH EDITION Chapter: 14 From Association to Causation: Deriving Inferences From Epidemiologic Studies,